Visual Grounding (VG) aims to ground a natural language description to the target object. The field has made tremendous progress in 2D images [1]}, [2]}, [3]}, [4]}. With the rapid development of 3D sensors and 3D vision technology, 3D visual grounding has recently attracted more attention, with wide applications including vision-language navigation [5]}, [6]}, intelligent agents [7]}, [8]}, and autonomous vehicles [9]}, [10]}. Compared to 2D visual grounding, the 3D task has more complex input data (e.g., sparse point clouds) and more variant spatial relationships, switching the output from grounding to 2D regions to 3D objects.
